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This paper proposes a framework for assessing whether misspecified decision
makers would be willing to pay for information that can potentially
make them less misspecified. We introduce a prior-free approach, based on
“constrained” maximal regret, to derive an upper bound on the subjective
assessment of potential gains from acquiring a more accurate model. The
constraint stems from the information currently available to the decision
maker. We apply our approach to three prominent models of misspecified
beliefs: coarse expectations, causal misperceptions and sampling equilibria.
